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. 2018 Dec 31;19(Suppl 10):913. doi: 10.1186/s12864-018-5280-y

Genotype- and tissue-specific miRNA profiles and their targets in three alfalfa (Medicago sativa L) genotypes

Robert Pokoo 1, Shuchao Ren 2, Qingyi Wang 2, Christy M Motes 3, Timothy D Hernandez 3, Sayvan Ahmadi 1, Maria J Monteros 3, Yun Zheng 2,4,✉, Ramanjulu Sunkar 1,✉
PMCID: PMC6311939  PMID: 30598106

Abstract

Background

Alfalfa (Medicago sativa L.) is a forage legume with significant agricultural value worldwide. MicroRNAs (miRNAs) are key components of post-transcriptional gene regulation and essentially regulate many aspects of plant growth and development. Although miRNAs were reported in alfalfa, their expression profiles in different tissues and the discovery of novel miRNAs as well as their targets have not been described in this plant species.

Results

To identify tissue-specific miRNA profiles in whole plants, shoots and roots of three different alfalfa genotypes (Altet-4, NECS-141and NF08ALF06) were used. Small RNA libraries were generated and sequenced using a high-throughput sequencing platform. Analysis of these libraries enabled identification of100 miRNA families; 21 of them belong to the highly conserved families while the remaining 79 families are conserved at the minimum between M. sativa and the model legume and close relative, M. truncatula. The profiles of the six abundantly expressed miRNA families (miR156, miR159, miR166, miR319, miR396 and miR398) were relatively similar between the whole plants, roots and shoots of these three alfalfa genotypes. In contrast, robust differences between shoots and roots for miR160 and miR408 levels were evident, and their expression was more abundant in the shoots. Additionally, 17 novel miRNAs were identified and the relative abundance of some of these differed between tissue types. Further, the generation and analysis of degradome libraries from the three alfalfa genotypes enabled confirmation of 69 genes as targets for 31 miRNA families in alfalfa.

Conclusions

The miRNA profiles revealed both similarities and differences in the expression profiles between tissues within a genotype as well as between the genotypes. Among the highly conserved miRNA families, miR166 was the most abundantly expressed in almost all tissues from the three genotypes. The identification of conserved and novel miRNAs as well as their targets in different tissues of multiple genotypes increased our understanding of miRNA-mediated gene regulation in alfalfa and could provide valuable insights for practical research and plant improvement applications in alfalfa and related legume species.

Introduction

Alfalfa (Medicago sativa L.) is an important forage legume species with global adaptation, high forage quality and the capacity for harvesting biomass multiple times during the growing season. Alfalfa is an autotetraploid (2n = 4x = 32), perennial outcrossing species with high levels of genetic diversity in cultivated and non-cultivated populations. Besides its use as a forage, alfalfa also has potential crop for biofuel production [1]. Alfalfa has the capacity for symbiotic nitrogen fixation and can also contribute to reduce soil erosion [2, 3].

Endogenous non-coding RNAs of approximately 21–22 nucleotides represent plant miRNAs that silence gene expression by binding to complementary sequences of its target mRNA at the post-transcriptional level. Such targeting results in mRNA cleavage and degradation or repression of translation, with the former being more prevalent in plants [4–7]. The miRNA analyses in different plant species highlight the important regulatory roles of miRNAs in multiple organs (roots, stems, leaves and flowers), differentiation and development, leaf polarity, transition from juvenile to vegetative stages and vegetative to reproductive phases, and regulation of plant responses to biotic and abiotic stresses [8–10].

Several investigations have shown that plant miRNAs can be classified into conserved and novel lineage- or species-specific miRNAs. Conserved miRNAs and their corresponding target genes are commonly found in all or most angiosperms, with some also being described in gymnosperms as well as primitive land plants such as ferns [11, 12]. However, miRNA analysis in several legumes including M. truncatula, soybean (Glycine max L), chickpea (Cicer arietinum L.), common bean (Phaseolus vulgaris), and Lotus japonicus indicate the presence of miRNAs that seem to be specific to certain legumes and there could have important gene regulatory roles [13–19]. Although recent attempts were made to report miRNAs from alfalfa (M. sativa) [20–22], these do not include the discovery of novel miRNAs, and most importantly, the miRNA target genes have not been confirmed in this legume species. Understanding miRNAs and their target gene regulation in various tissues can provide further insights into the miRNA target networks operating in a tissue-specific manner in alfalfa.

In order to identify conserved miRNAs as well as novel miRNAs from alfalfa, we constructed and sequenced small RNA libraries from whole clonally propagated plants, roots and shoots of three alfalfa genotypes (Altet-4, NECS-141 and NF08ALF06). The sequenced reads were mapped to known miRNAs in M. truncatula, deposited in the miRBase to identify and annotate the miRNAs in alfalfa. Degradome libraries were constructed and sequenced from these three genotypes to characterize the miRNA gene targets.

Materials and methods

Plant materials and growth conditions

Three alfalfa genotypes NECS-141, Altet-4 and NF08ALF06 were evaluated in this study. NECS-141 is the genotype being used to sequence the tetraploid alfalfa genome [23]. Altet-4 is an aluminum tolerant genotype used to develop a mapping population [24]. NF08ALF06 is a commercial breeding line with good agronomic performance (Forage Genetics International). The three alfalfa genotypes (NECS-141, Altet-4 and NF08ALF06) were clonally propagated and grown in tissue culture. After 13 d of growth in rooting media, these were transferred to medium at pH 7 for 96 h as previously described [25]. The rooting media contains 0.55 g/L Murashige & Skoog Basal Medium with Vitamins (PhytoTechnology #M519), 1 ml Plant Preservative Mixture, PPM (PhytoTechnology), adjust the pH to 5.8, and add 12 g/L Gelzan. The plants were placed in a Conviron growth chamber (24 °C, 18 h /6 h day/night cycle, 100 μmol light intensity) for root development and growth. An additional 20 clonally propagated plants of these genotypes were grown in a Conviron growth chamber as previously described and used to evaluate the tissue-specific expression of the miRNAs. Tissue samples were harvested and immediately flash frozen in liquid nitrogen and stored at − 80 °C.

Small RNA library construction and sequencing

Total RNA was isolated from the whole plants, roots and shoots of three alfalfa genotypes using TRIzol ® Reagent (Invitrogen), according to the manufacturer’s instructions. The quality of total RNA was monitored on 1% agarose gel and their concentrations were measured using Nanodrop spectrophotometer. Small RNA libraries were generated as described previously [26] by following the protocol described for the Illumina Truseq® Small RNA Preparation kit (Illumina, San Diego, USA). Briefly, 1 μg total RNA per sample was ligated sequentially with 5′ and 3’ RNA adaptors. The ligated products were converted into cDNAs and then amplified using PCR. The amplified products were sequenced using an Illumina Hiseq® Analyzer.

Identification of conserved and novel miRNAs

The raw sequencing reads were processed as follows: adaptor sequences were trimmed off from the raw reads to obtain small RNAs. These reads were then mapped to ribosomal RNA (rRNA), transfer RNA (tRNA), small nuclear RNAs (snRNA), and the aligned and mapped reads were not used for further analysis. The remaining reads were aligned to miRBase v 20 [27] to identify miRNAs in M. sativa. The reads with 100% sequence identity were designated as conserved miRNA homologs. To identify novel miRNAs, the presence of the miRNA-star (miRNA*) sequences coupled with the predictable hairpin-like structure for the precursor sequences were used.

Degradome library construction and analyses

Degradome libraries from the alfalfa genotypes NECS-141, Altet-4 and NF08ALF06 were constructed as previously described to identify potential target mRNAs [28]. Briefly, the cleaved 5′ monophosphate containing polyadenylated mRNA fragments were ligated to an RNA oligo-nucleotide adapter containing MmeI recognition site at its 3′ end. The ligated products were converted into cDNA using reverse transcriptase and the product was amplified using only 5 PCR cycles. The PCR product was eluted, digested with MmeI restriction enzyme and then ligated to a double-stranded DNA adapter. The ligated product was again purified and amplified using 15 cycles of PCR. The final PCR product was sequenced. The reads were processed for quality and then aligned to the transcriptome assembly of M. truncatula to identify potential miRNA targets using the SeqTar pipeline [29].

Results and discussion

The analyses of small RNA libraries

High-throughput sequencing has been used to identify miRNAs and their target mRNAs in plants [15, 30, 31]. To catalogue conserved and novel miRNAs in alfalfa, a total of eight small RNA libraries from the whole plants, roots and shoots of Altet-4, NECS-141 and NF08ALF06 genotypes were constructed and sequenced. After removal of the adapter sequences and low-quality reads, the total reads ranging between 11 to 42 million, and unique reads ranging between 1.8 to 8.5 million reads from these nine libraries were obtained (Table 1). However, the quality of the small RNA library generated from the shoots of NF08ALF06 did not meet the threshold criteria, therefore only NECS-141 and Altet-4 were used for the miRNA analyses of shoot tissues.

Table 1.

The mapping of total and unique reads obtained from different small RNA libraries

Altet-4 whole plants NECS-141 whole plants NF08ALF06 whole plants Altet-4 Roots NECS-141 Roots NF08ALF06 Roots Altet-4 Shoots NCES-141 Shoots
Total reads Unique reads Total reads Unique reads Total reads Unique reads Total reads Unique reads Total reads Unique reads Total reads Unique reads Total reads Unique reads Total reads Unique reads
cdna 6,858,719 336,266 6,197,308 430,819 8,142,985 493,929 9,352,477 276,276 19,665,339 732,738 8,930,063 352,167 17,117,689 909,491 10,943,411 669,572
ncRNAs 6,810,937 261,134 5,666,067 213,396 7,722,727 284,785 9,633,993 271,496 18,454,661 272,596 8,834,028 237,827 14,718,199 289,087 7,855,629 128,514
pre-miRBase 567,518 3182 943,976 3888 1,162,233 4005 147,326 2409 1,102,879 5780 426,327 3213 2,520,492 7051 3,840,771 6449
repeats 5,451,840 162,552 4,218,992 148,297 5,756,349 183,418 8,267,063 158,310 15,744,403 180,030 7,536,403 146,043 10,855,687 192,377 3,798,312 104,708
genome 8,951,430 1,142,594 9,878,838 2,398,705 11,387,413 2,053,582 11,557,742 784,140 29,143,549 5,078,322 11,588,832 1,488,546 28,744,231 5,246,027 29,192,098 5,834,731
total 12,008,892 2,343,120 11,645,217 3,348,188 15,733,102 3,739,163 14,377,336 1,860,736 33,335,201 6,947,622 14,378,859 2,708,737 42,196,888 8,564,218 34,441,313 7,748,996
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Quantification of miRNA abundances between the genotypes and tissues was preceded by normalizing the expression levels of miRNA families to reads per ten million (RPTM). The normalized miRNA family read frequencies ranged between 1 to 552,267 RPTM for the whole plants, between 1 to 134,679 RPTM for the root samples, and 1 to 165,310 RPTM for the shoot samples (Table 2). The range of miRNA read frequencies varied slightly between the three genotypes. As expected, the most conserved miRNAs appeared to be the most abundantly expressed in all tissues and genotypes, with the exception of miR169, miR393, miR395 and miR172 which exhibited low abundances. Specifically, miR172 levels in roots and shoots of the three genotypes were extremely low and in most cases was below 20 RPTM (Table 2). The miRNA families with the lowest expression levels, and in some cases as low as 1 RPTM, were largely represented by the non-conserved miRNAs or miRNAs that have been reported exclusively from M. truncatula (miRBase) that include miR2601, miR2674, miR5207, miR5241, miR5243, miR5244, miR5255, miR5257, miR5269, miR5282, miR5289, miR5294, miR5296, miR5299, miR5561, miR5744, and miR7701 (Table 2). miR5207 is the only miRNA that was also reported from Gossypium raimondii (miRBase). The majority of the miRNA families identified are 21 nt long, although some cases including miR2601 and miR2603 were represented by 22 nucleotides. Further, a total of 23 miRNA families included between miR5267 to miR5299 were 24 nt long. The fact that these small RNAs were initially identified in M. truncatula (miRBase), and could be identified in several independent small RNA libraries from three different alfalfa genotypes (Table 2), suggests that these sequences and their associated processing are conserved between alfalfa and its close relative M. truncatula. However, their extremely low abundances coupled with their longer read lengths could also indicate that these may be 24-nt long siRNAs. Additional studies are needed to assess the precise nature of these small RNAs, i.e., miRNAs or siRNAs.

Table 2.

Identified miRNA families and their frequencies (reads per ten million [RPTM]) in whole plants, roots and shoots of three alfalfa genotypes (miRNA-stars were marked in bold)

Whole plants Roots Shoots
Altet-4 NECS-141 NF08ALF06 Altet-4 NECS-141 NF08ALF06 Altet-4 NECS-141
miR156-5p 4712 7243 6436 1001 3466 3145 19,808 47,306
miR156-3p 3262 4012 2992 545 755 548 4634 6420
miR159-3p 6315 11,050 8484 3910 23,465 10,549 61,929 103,370
miR160-5p 225 417 351 20 277 113 3505 8706
miR162-3p 140 229 292 194 454 361 533 517
miR164-5p 108 275 306 6 77 57 48 431
miR166-3p 336,905 552,267 534,054 34,634 111,596 134,679 101,118 131,196
miR166-5p 544 960 614 228 508 438 800 1216
miR167-5p 218 470 722 107 240 357 699 1389
miR167-3p 2 1 0 0 0 0 0 0
miR168-5p 1121 1980 1691 735 2960 1317 3460 5049
miR168-3p 672 691 768 182 443 194 5550 5638
miR169-5p 19 34 35 47 55 35 46 59
miR169-3p 7 12 5 6 18 7 2 2
miR171-3p 51 120 232 44 238 316 60 85
miR171e-5p 26 39 44 22 37 42 7 6
miR172-3p 62 138 240 0 1 1 2 3
miR172-5p 3 8 20 1 1 2 2 2
miR319-3p 1631 3689 2101 1607 6281 3323 4330 10,864
miR319-5p 46 72 74 3 20 14 129 559
miR390-5p 95 410 318 86 656 234 121 382
miR393-5p 11 24 34 4 8 10 22 45
miR395-3p 3 8 7 12 13 7 2 0
miR396-5p 12,185 21,926 22,411 2835 14,549 8121 39,236 58,336
miR396-3p 250 437 437 76 312 188 323 356
miR397-5p 57 28 15 37 16 11 94 61
miR398a-5p 19 16 25 0 2 1 4 3
miR398-3p 3814 3223 2272 2101 4086 3176 35,538 26,478
miR399-3p 17 11 11 25 26 13 62 43
miR408-3p 2656 1301 1096 977 737 570 6380 2866
miR408-5p 17 7 12 12 14 8 55 35
miR482-3p 28 27 49 18 19 45 41 105
miR482-5p 7 10 10 11 19 13 9 12
miR530-5p 2 7 8 0 1 1 2 4
miR1507–3 963 1789 1701 881 1596 1230 1778 3349
miR1510-5p 1959 4278 3520 523 3505 1429 12,496 34,705
miR1510-3p 96 151 167 52 118 63 256 617
miR2111 47 20 10 44 15 42 278 22
miR2118 5607 11,948 16,134 106 610 307 79,977 165,310
miR2199 95 15 42 21 18 30 156 13
miR2585 57 7 74 28 1 22 239 10
miR2587 0 6 9 0 10 10 13 28
miR2590 15 41 42 23 55 25 109 177
miR2592 393 1350 395 119 1612 268 1224 1742
miR2601-5p 0 0 0 0 0 0 1 1
miR2603-5p 0 8 1 1 1 1 5 24
miR2629-5p 2 5 4 1 3 7 2 5
miR2632-5p 0 1 0 0 0 0 1 18
miR2634-3p 5 3 7 6 4 15 9 6
miR2643-3p 1502 2689 2106 382 1462 948 9682 24,971
miR2651-3p 27 52 22 4 21 7 40 49
miR2661-5p 3 4 5 2 4 5 13 9
miR2666-3p 0 21 0 0 14 0 0 29
miR2674-3p 0 0 1 0 0 0 0 0
miR2678-3p 2 6 4 0 4 4 4 12
miR4414-3p 2 4 4 0 1 1 3 7
miR4414-5p 1 3 4 1 1 0 5 7
miR5037-5p 4 3 13 3 8 24 2 4
miR5204-3p 4 10 6 3 28 17 6 10
miR5205-5p 7 22 14 0 6 6 15 6
miR5207-5p 0 0 0 0 0 1 0 1
miR5208-3p 2 1 1 0 0 0 1 1
miR5208d-5p 0 0 1 0 1 0 1 1
miR5211-5p 432 85 23 559 71 41 292 59
miR5213-5p 801 836 887 181 891 829 1397 1379
miR5214-3p 63 155 153 97 414 452 153 201
miR5225-5p 4 2 8 3 1 8 1 1
miR5230-5p 1 2 1 0 1 0 6 1
miR5231-5p 10 7 7 3 11 1 43 69
miR5232-5p 67 253 419 56 503 417 602 3964
miR5237-3p 2 2 0 0 2 1 6 4
miR5238-5p 2 0 2 1 2 1 0 0
miR5239-5p 347 269 430 16 52 72 622 773
miR5241-3p 0 0 0 0 0 0 0 1
miR5243-3p 0 0 0 0 0 0 0 1
miR5244-3p 0 1 1 0 0 0 0 1
miR5248-5p 0 2 1 0 2 1 0 3
miR5255-3p 0 1 1 0 0 0 0 1
miR5257-5p 1 0 0 0 0 0 0 0
miR5261-3p 76 89 93 22 302 127 283 227
miR5266-5p 0 0 0 4 2 3 0 1
miR5267-5p 1 3 1 0 1 1 0 2
miR5269-3p 0 1 1 1 0 0 0 0
miR5271-5p 1 1 1 1 2 2 1 1
miR5272-5p 17 22 12 12 34 21 18 18
miR5273-3p 1 3 1 1 3 1 4 2
miR5277-3p 60 108 62 75 99 48 16 20
miR5279-5p 3 19 13 1 16 8 8 7
miR5281-3p 29 47 29 35 69 18 141 150
miR5282-3p 0 0 0 0 0 0 1 0
miR5284-3p 20 52 50 4 14 17 10 23
miR5285-5p 0 0 1 1 1 0 2 3
miR5286-3p 2 0 2 1 3 2 3 2
miR5287-3p 6 10 14 8 9 4 17 19
miR5289-3p 0 1 0 1 0 0 0 0
miR5290-3p 0 5 1 1 2 1 2 6
miR5291-3p 0 1 1 0 3 1 0 1
miR5292-3p 16 35 21 6 34 21 53 82
miR5294-3p 0 0 1 0 0 0 0 0
miR5295-3p 9 29 13 3 15 9 7 6
miR5296-3p 1 0 0 0 0 0 0 0
miR5297-3p 0 1 2 1 0 1 1 1
miR5298-3p 4 4 1 4 0 1 3 15
miR5299-3p 0 1 0 0 1 1 0 0
miR5558-5p 539 1938 1820 220 415 412 1103 1276
miR5559-5p 7 3 0 0 0 0 8 5
miR5561-3p 5 14 18 0 5 5 4 5
miR5561-5p 0 0 0 1 0 0 0 0
miR5743-5p 19 113 6 0 1 1 70 398
miR5744-5p 0 0 0 0 0 1 0 0
miR5745-3p 28 39 41 69 144 171 126 113
miR5752-3p 0 4 0 0 1 0 8 11
miR5754-5p 0 6 19 0 1 3 2 41
miR7696-5p 0 1 1 0 1 0 0 1
miR7696-3p 174 95 253 40 138 184 1173 255
miR7701-3p 0 1 0 0 0 0 0 0
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MicroRNA profiles in alfalfa plants, roots and shoots

A total of 100 known miRNA families were identified from the small RNA libraries of the three alfalfa genotypes (Table 2). Of these, 21 families were represented by the highly conserved miRNAs, whereas the remaining 79 families could be considered as Medicago-specific miRNA families. The identification of these 79 miRNA families in alfalfa was based on their expression in M. truncatula (miRbase), therefore, these are conserved at least between M. truncatula and alfalfa.

Among the highly conserved miRNA families, miR166 was the most highly expressed family in seven of the eight samples that were surveyed in this study. The only exception to this trend was observed in the shoots of NECS-141 in which the miR2118 family was the most abundant followed by the miR166 family. The miRNA families, miR396 and miR2118 represents the second and third most abundantly expressed in the whole plants, while miR159 and miR396 were the second and third most highly expressed miRNAs in roots. Several additional miRNA families including miR398, miR160, miR168, miR319, miR408, miR1510 and miR2643 were also highly expressed but miR169, miR171, miR393, miR397 and miR395 were expressed at relatively very low levels (Table 2). On the other hand, miR159, miR156, miR319, miR398 miR1507 and miR1510 were highly expressed but miR164, miR169, miR172, miR393, miR397, miR399 and miR482 were expressed at very low levels in roots of these genotypes. Interestingly, miR160 was not sequenced from the roots of three alfalfa genotypes.

Overall, the conserved miRNA families such as the miR156, miR159, miR166, miR168, miR319, miR396, miR398 and miR408 were more highly expressed in the plants, roots and shoots of all three alfalfa genotypes. Among the legume-specific families, miR1507, miR1510, miR2118, miR2592, miR2643, miR5213, miR5232, miR5558 and miR7696 (Table 2) were also abundant in all tissues of alfalfa genotypes. Conversely, some conserved miRNA families represented by miR169 and miR393 recorded very low abundances in all samples. Other notable differences between roots and shoots include relatively low expression levels of miR160, miR167, and miR408 in roots compared to the shoots of alfalfa genotypes (Table 2).

Several miRNA families including miR482, miR1507, miR2118, miR4416 are conserved in M. truncatula, soybean, chickpea (miRBase). These miRNA families are known to regulate NBS-LRR genes that are involved in pathogen resistance. The miRNA-guided cleavage on the NBS-LRR genes initiates the generation of phasiRNAs [16, 18, 32]. In alfalfa, miR482, miR1507 and miR2118 were detected in all three tissues (Table 2), but not miR4416. Both miR2118 and miR1507 families were more abundantly expressed in all tissues and genotypes compared with miR482 family. Remarkably, miR2118 was the top most highly expressed miRNA family in shoots of NECS-141. By contrast, miR2118 levels were very low in roots of three alfalfa genotypes. On the other hand, miR1507 family displayed approximately similar levels in three tissues of alfalfa genotypes.

The miRNA-star sequences corresponding to the 12 of the 21 highly conserved miRNA families were also recovered from almost all libraries (Table 2). Additionally, miRNA-stars for the miR1510, miR4414, miR5208, and miR7696 were also detected. Furthermore, the miRNA-star expression levels for miR156, miR166 and miR168 were very high (Table 2). Intriguingly, like miR168, miR168 star levels differed greatly between different tissue. In shoots of NECS-141, miR168 star levels were slightly more than that of miR168, while both in whole plants and roots, the star levels were approximately half of the levels of miR168.

miRNA diversity in alfalfa compared with other legumes

Several miRNA families are specifically reported from the leguminous plants such as the M. truncatula, Glycine max, Lotus japonicus, Phaseolus vulgaris, Cicer arietinum, Vigna unguiculata and Acacia auriculiformis [14, 16, 18, 19, 32, 33]. These lineage-specific miRNAs include miR1507, miR1508, miR1509, miR1510, miR1512, miR1514, miR1520, miR1521, miR2118, miR2086, miR2109, miR2199, miR4414, miR5213, miR5232, and miR5234 among others (miRBase). The majority of these were reported from M. truncatula and soybean, since these legume species have been the subject of multiple studies exploring small RNAs. Most of these legume-specific miRNAs were also identified in alfalfa and a few of them including miR1507, miR1510, miR2118, miR2592, miR2643, miR5211, miR5213, miR5214, miR5232, miR5239, miR5277, miR5558, and miR7696 were specifically highly expressed in all three genotypes (Table 2).

Identification of novel miRNAs from alfalfa

The sequencing of the small RNAs from multiple tissues of three different alfalfa genotypes would allow us to identify the novel miRNAs more confidently. Novel miRNA identification was dependent on sequencing of the miRNA complementary strand (miRNA-star) coupled with the predictable fold back structure for the primary miRNA transcript. Because a stable assembly of the tetraploid alfalfa genome sequence is not available, the small RNAs were mapped to the M. truncatula genome. Mapping of the small RNAs from the three alfalfa genotypes onto the M. truncatula genome enabled the identification of novel miRNAs more confidently because they have been sequenced from M. sativa and mapped on to the M. truncatula, suggesting their conservation between M. sativa and M. truncatula. Moreover, the novel miRNA identification in this study is more robust as it includes sequencing of these small RNAs from three different genotypes. We have identified a total of 17 novel miRNAs which have been sequenced from all of the three genotypes (Table 3 and Fig. 1). Among these, t50582913 was highly expressed followed by t50063038. In roots, t50582913 was highly expressed in NECS-141 and Altet-4 but not in NF08ALF06. In shoots, t50063038 was highly expressed followed by the t50582913 and t51235783.

Table 3.

Identified novel miRNAs based on sequencing both 5′ and 3′ reads and the most abundant ones that is marked in bold denotes potential novel miRNA based on their greater abundances

miR-5p miR-5p_seq miR-3p miR-3p_seq Altet-4 Plants NECS-141 Plants NF08ALF06 Plants Altet-4 Roots NECS-141 Roots NF08ALF06 Roots Altet-4 Shoots NECS-141 Shoots
t61680599 UUUCUUUGACUGGUUUUUGAAU t21108041 CAAAAGCCUGUCAAUGAAAAUG 0 31 0 0 312 0 0 32
t46402976 UAGCAUCAAGCGUCGCGUCGAU t28372577 CGACCCGAGGCUUAUGCGAUC 115 97 145 81 479 229 335 315
t59820880 UUGGCAGAAUCACGGUGUGCC t29809748 CGGUGGCAUCGUGAUUUUGAC 0 6 25 1 6 8 1 47
t21870702 CAACUCGGUCCUUCUGUUAAC t44359413 UAACAGAAGGACUGAGUUGCC 0 11 3 1 41 12 24 103
t62603216 UUUUCAAGUUGGUCCCUUACG t44814359 UAAGGGACCAACUUGAAAACU 77 178 196 7 240 107 529 899
t8901469 ACCUGGAGACAGAGAUGCAAU t45832108 UACGUCUCUGUCUUUCGGGUUG 1 55 28 2 222 28 6 247
t12927907 AGGAUAACAAUGUUGCAUAAG t47767430 UAUGUAGCACUGUUUUUCUGA 13 43 85 14 273 147 83 262
t63076572 UUUUUAGAUACAUUGAAUAAU t47960370 UAUUCAAUGUAUCUAAAAAG 10 10 14 4 40 2 208 177
t53501433 UGAUUAUUCUACUACCCGGACC t50063038 UCCGGGUAGCAGAAUAAUCAUC 350 371 78 45 371 18 17,057 20,494
t12458129 AGCGGUUGGUACAAUGCAAUAu t50582913 UCGCCUUGUACCAACCUACUGC 544 915 0 123 1148 0 881 1453
t40560414 GGUCCUGAUGUUUUUUAGAGC t51235783 UCUCAAAGACAUAAGGAACCUC 19 281 0 24 762 0 269 1655
t55270980 UGUCUUUAGCUUCCGAAACAa t55621674 UGUUCCGGUAGAUGAAGUCAC 4 4 0 2 23 0 24 40
t14211567 AGUUAAUUGUGUUGCAUGAGUU t57726911 UUCAGCAACAUGAGUUAACUCA 17 26 60 3 48 22 42 50
t8194733 ACAUUUUAGAUUGUUGAGGAA t27568341 CCUCAAUUAUCUAUUAUGUUU 0 0 3 0 3 6 6 0
t62313817 UUUGUUAAACAUUUGUUUCC t311560 AAAACAAAUGUUUAGCUAAG 0 6 0 0 15 1 0 12
t55268921 UGUCUUGGUUUCAAAAAGAAGu t52170136 UCUUUUUGCAAACCAACUCAAU 4 19 13 1 29 4 9 56
t51870988 UCUUAUUUUCGACAUUGCAAAG t59475847 UUGCAGGUCGAGAAUAAAAUG 19 99 71 1 9 1 353 1072
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Fig. 1.

Fig. 1

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The predicted foldback structures using the novel miRNA precursor sequences. a The fold-back structures for six novel miRNAs. b The distribution of small RNA reads on the precursors of the novel miRNAs depicted in Fig. 1a

Identification of miRNA targets in alfalfa

Although the alfalfa is one of the important legumes agronomically, the genome sequencing and annotations are not available so far. Due to this, studies have utilized the well-studied and closely related M. truncatula genome annotations as a model for alfalfa studies. The nucleotide identity for some genes was greater than 97% between M. sativa and M. truncatula [34]). Thus, using M. truncatula transcript annotations can facilitate identification of miRNA targets in alfalfa. We used SeqTar algorithm (Zheng et al., 2012) to identify miRNA targets by allowing a maximum of 4 mismatches between miRNAs and their potential target transcripts.

Previous studies have revealed that conserved miRNAs are strongly associated with the regulation of genes that encode transcription factors [35]. These transcription factors in turn regulate key developmental processes and pathways in plants. Degradome sequencing has been very effective in identifying plant miRNA targets. Besides identifying the conserved targets, this approach can also identify non-conserved targets for the conserved miRNAs [28, 36, 37]. Degradome sequencing was used in this study to identify the cleaved mRNA fragments corresponding to the miRNA recognition sites in all three alfalfa genotypes. Approximately 30 million degradome reads were obtained from the transcripts of each of the alfalfa genotypes (Table 4) and these reads were analysed using SeqTar program. In total, we have identified 69 targets for 31 miRNA families that included 16 highly conserved families (Table 5). With respect to the conserved miRNAs, 33 targets for 16 conserved miRNA families were identified (Table 5). The known targets for miR162, miR165/166, miR398 and miR399 families were not identified in this study. Although miR165/166 family is the most abundantly expressed as scored from their read frequencies in almost all libraries but the cleaved fragments from the HD-Zip target transcripts were not recovered from degradome libraries of alfalfa genotypes.

Table 4.

Mapping of the reads obtained from the degradome libraries

Database Altet-4 NECS-141 NF08ALF06
Total reads Unique reads Total reads Unique reads Total reads Unique reads
M. truncatula genome 852,790 487,582 1,541,055 791,294 3,091,832 1,021230
M. sativa genome 1,488,681 957,866 2,691,763 1,435,659 4,591,130 1,877,041
Cds 770,970 426,278 1,436,059 727,330 2,928,098 933,425
ncRNA 231,076 22,907 186,813 18,014 1,305,681 36,585
Repeats 171,358 16,804 116,741 16,759 636,675 23,958
Pre-miRBase 34,631 837 35,979 1045 50,136 1192
Total 28,674,678 2,286,693 30,573,270 3,137,327 30,812,606 3,885,547
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Table 5.

miRNA targets identified in the degradome libraries generated from three alfalfa genotypes. #Mis. is number of mismatches on the miRNA complementary site; Valid reads is Reads corresponding to the expected cleavage site; Total reads is Total reads mapped to the cDNA of the gene; Percent is Percent reads at the expected cleavage site

genotypes miRNA id# Target gene #Mis. Valid reads Total reads Percent Target gene annotation
Altet-4 miR156e Medtr7g028740.2 0 4 23 17.4 squamosa promoter-binding-like protein
Altet-4 miR156a Medtr7g444860.1 0 2 28 7.1 squamosa promoter-binding-like protein
Altet-4 miR156a Medtr3g099080.1 0 1 3 33.3 squamosa promoter-binding 13A-like protein
Altet-4 miR159b Medtr8g042410.1 2.5 1 16 6.3 MYB transcription factor
Altet-4 miR160c Medtr2g094570.3 1 4 21 19.1 auxin response factor 1
Altet-4 miR164d Medtr2g064470.1 1 2 34 5.9 NAC transcription factor-like protein
Altet-4 miR164d Medtr8g058330.1 2 5 49 10.2 protein transporter Sec61 subunit alpha-like protein
Altet-4 miR167b-5p Medtr8g079492.3 4 4 62 6.5 auxin response factor 2
Altet-4 miR169e-5p Medtr2g099490.2 2 1 20 5 CCAAT-binding transcription factor
Altet-4 miR171f Medtr0092s0100.2 1.5 5 24 20.8 GRAS family transcription regulator
Altet-4 miR172a Medtr4g094868.3 1 1 13 7.7 AP2 domain transcription factor
Altet-4 miR172a Medtr5g016810.2 1 1 18 5.6 AP2 domain transcription factor
Altet-4 miR172a Medtr2g093060.3 0 4 17 23.5 AP2-like ethylene-responsive transcription factor
Altet-4 miR319d-3p Medtr2g078200.1 3 2 34 5.9 TCP family transcription factor
Altet-4 miR319d-3p Medtr8g463380.1 3 2 7 28.6 TCP family transcription factor
Altet-4 miR393a Medtr1g088950.1 1 11 83 13.3 transport inhibitor response-like protein
Altet-4 miR393a Medtr7g083610.1 2 38 134 28.4 transport inhibitor response 1 protein
Altet-4 miR395j Medtr1g102550.1 1 1 76 1.3 ATP sulfurylase
Altet-4 miR396b-5p Medtr1g017490.2 3 47 100 47 growth-regulating factor
Altet-4 miR396b-5p Medtr2g041430.3 3 5 12 41.7 growth-regulating factor-like protein
Altet-4 miR396b-5p Medtr5g027030.1 3 5 15 33.3 growth-regulating factor
Altet-4 miR396a-5p Medtr3g052060.1 2 1 1 100 hypothetical protein
Altet-4 miR398c Medtr4g114870.1 3 8 23 34.8 plastocyanin-like domain protein
Altet-4 miR398a-3p Medtr8g064810.1 3 5 36 13.9 protein disulfide isomerase (PDI)-like protein
Altet-4 miR408-3p Medtr8g089110.1 3 3 9 33.3 basic blue-like protein
Altet-4 miR408-3p Medtr8g007020.1 3.5 5 73 6.9 plastocyanin-like domain protein
Altet-4 miR408-3p Medtr8g007035.1 3.5 5 123 4.1 plastocyanin-like domain protein
Altet-4 miR408-5p Medtr3g074830.1 3.5 2 442 0.5 phosphate-responsive 1 family protein
Altet-4 miR1510a-5p Medtr2g012770.1 1 1 5 20 disease resistance protein (TIR-NBS-LRR class)
Altet-4 miR2199 Medtr7g080780.2 2 2 8 25 helix loop helix DNA-binding domain protein
Altet-4 miR2643a Medtr3g010590.1 1 1 15 6.7 F-box protein interaction domain protein
Altet-4 miR2643a Medtr6g053240.1 3 2 4 50 F-box protein interaction domain protein
Altet-4 miR4414a-5p Medtr3g117120.1 4 3 84 3.6 BZIP transcription factor bZIP124
Altet-4 miR5213-5p Medtr6g084370.1 2 1 2 50 disease resistance protein (TIR-NBS-LRR class)
Altet-4 miR5213-5p Medtr6g088245.1 3 1 5 20 disease resistance protein (TIR-NBS-LRR class)
Altet-4 miR5239 Medtr3g018680.1 3 1 5 20 F-box/RNI superfamily protein, putative
Altet-4 miR5561-3p Medtr2g045295.1 3 1 4 25 hypothetical protein
Altet-4 miR5752b Medtr8g066820.1 4 9 423 2.1 PLATZ transcription factor family protein |
Altet-4 miR7696a-5p Medtr1g072130.1 3 2 27 7.4 PHD finger protein, putative
Altet-4 miR7696c-3p Medtr3g081480.1 3 2 21 9.5 endoplasmic reticulum vesicle transporter
Altet-4 miR7696d-5p Medtr3g112250.1 3.5 8 36 22.2 hypothetical protein
Altet-4 miR7696c-3p Medtr4g011600.2 3.5 1 26 3.9 sulfate transporter-like protein
Altet-4 miR7696c-3p Medtr7g085650.4 3.5 1 6 16.7 sulfate adenylyltransferase subunit 1/adenylylsulfate kinase
Altet-4 miR7701-3p Medtr6g011380.2 2 1 137 0.7 SPFH/band 7/PHB domain membrane-associated family protein
NF08ALF06 miR156e Medtr7g028740.2 0 14 36 38.9 squamosa promoter-binding-like protein
NF08ALF06 miR156a Medtr7g444860.1 0 1 144 0.7 squamosa promoter-binding-like protein
NF08ALF06 miR156h-3p Medtr7g091370.1 3 1 11 9.1 heat shock transcription factor
NF08ALF06 miR159b Medtr8g042410.1 2.5 4 30 13.3 MYB transcription factor
NF08ALF06 miR160c Medtr2g094570.3 1 8 46 17.4 auxin response factor 1
NF08ALF06 miR160d Medtr1g064430.2 0.5 3 24 12.5 auxin response factor 1
NF08ALF06 miR160d Medtr3g073420.1 0.5 2 17 11.8 auxin response factor, putative
NF08ALF06 miR164d Medtr2g064470.1 1 41 151 27.2 NAC transcription factor-like protein
NF08ALF06 miR164d Medtr8g058330.1 2 5 115 4.4 protein transporter Sec61 subunit alpha-like protein
NF08ALF06 miR167b-5p Medtr8g079492.3 4 9 133 6.8 auxin response factor 2
NF08ALF06 miR167a Medtr4g076020.1 3.5 5 77 6.5 GRAS family transcription factor
NF08ALF06 miR171f Medtr0092s0100.2 1.5 60 115 52.2 GRAS family transcription regulator
NF08ALF06 miR172a Medtr4g094868.3 1 1 45 2.2 AP2 domain transcription factor
NF08ALF06 miR172a Medtr5g016810.2 1 1 84 1.2 AP2 domain transcription factor
NF08ALF06 miR172a Medtr2g093060.3 0 4 35 11.4 AP2-like ethylene-responsive transcription factor
NF08ALF06 miR172a Medtr4g061200.4 1 1 28 3.6 AP2-like ethylene-responsive transcription factor
NF08ALF06 miR172a Medtr7g100590.1 1 2 17 11.8 AP2 domain transcription factor
NF08ALF06 miR319d-3p Medtr2g078200.1 3 2 126 1.6 TCP family transcription factor
NF08ALF06 miR319d-3p Medtr8g463380.1 3 2 48 4.2 TCP family transcription factor
NF08ALF06 miR393a Medtr1g088950.1 1 54 268 20.2 transport inhibitor response-like protein
NF08ALF06 miR393a Medtr7g083610.1 2 472 771 61.2 transport inhibitor response 1 protein
NF08ALF06 miR393a Medtr8g098695.2 4 1 46 2.2 transport inhibitor response 1 protein
NF08ALF06 miR396b-5p Medtr1g017490.2 3 423 742 57 growth-regulating factor
NF08ALF06 miR396b-5p Medtr2g041430.3 3 30 75 40 growth-regulating factor-like protein
NF08ALF06 miR396b-5p Medtr5g027030.1 3 10 42 23.8 growth-regulating factor
NF08ALF06 miR396a-5p Medtr3g011560.1 3 1 3 33.3 TNP1
NF08ALF06 miR396a-5p Medtr3g052060.1 2 3 11 27.3 hypothetical protein
NF08ALF06 miR396a-5p Medtr8g017000.1 3 1 2 50 Ulp1 protease family, carboxy-terminal domain protein
NF08ALF06 miR398c Medtr4g114870.1 3 14 49 28.6 plastocyanin-like domain protein
NF08ALF06 miR398a-3p Medtr8g064810.1 3 8 44 18.2 protein disulfide isomerase (PDI)-like protein
NF08ALF06 miR408-3p Medtr8g089110.1 3 8 34 23.5 basic blue-like protein
NF08ALF06 miR408-3p Medtr8g007020.1 3.5 10 375 2.7 plastocyanin-like domain protein
NF08ALF06 miR408-3p Medtr8g007035.1 3.5 10 675 1.5 plastocyanin-like domain protein
NF08ALF06 miR408-5p Medtr3g074830.1 3.5 27 948 2.9 phosphate-responsive 1 family protein
NF08ALF06 miR482-5p Medtr1g064430.2 3.5 1 24 4.2 auxin response factor 1
NF08ALF06 miR530 Medtr3g072110.1 2.5 3 102 2.9 transmembrane amino acid transporter family protein
NF08ALF06 miR1507–3p Medtr8g036195.1 2 4 9 44.4 NBS-LRR type disease resistance protein
NF08ALF06 miR1510a-5p Medtr7g108860.4 3.5 21 1061 2 CS domain protein
NF08ALF06 miR2199 Medtr7g080780.2 2 1 26 3.9 helix loop helix DNA-binding domain protein
NF08ALF06 miR2643a Medtr6g053240.1 3 25 33 75.8 F-box protein interaction domain protein
NF08ALF06 miR4414a-5p Medtr3g117120.1 4 8 260 3.1 BZIP transcription factor bZIP124
NF08ALF06 miR5037c Medtr4g070550.1 3 2 44 4.6 F-box protein interaction domain protein
NF08ALF06 miR5213-5p Medtr4g014580.1 1.5 3 31 9.7 TIR-NBS-LRR class disease resistance protein
NF08ALF06 miR5238 Medtr3g077740.2 2.5 1 259 0.4 pantothenate kinase
NF08ALF06 miR5239 Medtr3g018680.1 3 4 43 9.3 F-box/RNI superfamily protein, putative
NF08ALF06 miR5561-3p Medtr2g045295.1 3 1 12 8.3 hypothetical protein
NF08ALF06 miR5752a Medtr8g066820.1 4 13 936 1.4 PLATZ transcription factor family protein
NF08ALF06 miR7696a-5p Medtr1g072130.1 3 4 259 1.5 PHD finger protein, putative
NF08ALF06 miR7696c-3p Medtr3g081480.1 3 2 46 4.4 endoplasmic reticulum vesicle transporter
NF08ALF06 miR7696c-5p Medtr7g076830.1 3 3 103 2.9 DEAD-box ATP-dependent RNA helicase-like protein
NF08ALF06 miR7696d-5p Medtr3g112250.1 3.5 5 30 16.7 hypothetical protein
NF08ALF06 miR7696c-3p Medtr4g011600.2 3.5 1 103 1 sulfate transporter-like protein
NF08ALF06 miR7696c-3p Medtr7g085650.4 3.5 2 10 20 sulfate adenylyltransferase subunit 1/adenylylsulfate kinase
NF08ALF06 miR7701-3p Medtr3g108910.1 2.5 2 375 0.5 hypothetical protein
NF08ALF06 miR7701-3p Medtr6g011380.2 2 2 86 2.3 SPFH/band 7/PHB domain membrane-associated family protein
NCES-141 miR156e Medtr7g028740.2 0 18 46 39.1 squamosa promoter-binding-like protein
NCES-141 miR156a Medtr7g444860.1 0 4 101 4 squamosa promoter-binding-like protein
NCES-141 miR156a Medtr8g096780.1 0 1 11 9.1 squamosa promoter-binding 13A-like protein
NCES-141 miR156a Medtr3g085180.1 1 1 2 50 squamosa promoter-binding-like protein
NCES-141 miR156h-3p Medtr7g091370.1 3 2 5 40 heat shock transcription factor
NCES-141 miR159b Medtr8g042410.1 2.5 3 36 8.3 MYB transcription factor
NCES-141 miR160c Medtr2g094570.3 1 12 37 32.4 auxin response factor 1
NCES-141 miR164d Medtr2g064470.1 1 33 100 33 NAC transcription factor-like protein
NCES-141 miR164d Medtr8g058330.1 2 14 119 11.8 protein transporter Sec61 subunit alpha-like protein
NCES-141 miR167b-5p Medtr8g079492.3 4 10 101 9.9 auxin response factor 2
NCES-141 miR167a Medtr4g076020.1 3.5 4 45 8.9 GRAS family transcription factor
NCES-141 miR167b-3p Medtr4g124900.2 3.5 1 154 0.7 auxin response factor 2
NCES-141 miR168a Medtr6g477980.2 4 2 245 0.8 argonaute protein 1A
NCES-141 miR171f Medtr0092s0100.2 1.5 36 70 51.4 GRAS family transcription regulator
NCES-141 miR172a Medtr4g094868.3 1 2 50 4 AP2 domain transcription factor
NCES-141 miR172a Medtr5g016810.2 1 2 56 3.6 AP2 domain transcription factor
NCES-141 miR172a Medtr2g093060.3 0 1 19 5.3 AP2-like ethylene-responsive transcription factor
NCES-141 miR172a Medtr4g061200.4 1 3 32 9.4 AP2-like ethylene-responsive transcription factor
NCES-141 miR319d-3p Medtr2g078200.1 3 1 55 1.8 TCP family transcription factor
NCES-141 miR319d-3p Medtr8g463380.1 3 1 26 3.9 TCP family transcription factor
NCES-141 miR393a Medtr1g088950.1 1 38 222 17.1 transport inhibitor response-like protein
NCES-141 miR393a Medtr7g083610.1 2 337 539 62.5 transport inhibitor response 1 protein
NCES-141 miR395j Medtr1g102550.1 1 1 163 0.6 ATP sulfurylase
NCES-141 miR396b-5p Medtr1g017490.2 3 201 352 57.1 growth-regulating factor
NCES-141 miR396b-5p Medtr5g027030.1 3 6 16 37.5 growth-regulating factor
NCES-141 miR396b-5p Medtr8g020560.1 3 1 7 14.3 growth-regulating factor-like protein
NCES-141 miR396a-5p Medtr3g011560.1 3 1 1 100 TNP1
NCES-141 miR396a-5p Medtr8g017000.1 3 1 1 100 Ulp1 protease family, carboxy-terminal domain protein
NCES-141 miR397-5p Medtr7g062310.1 1.5 2 4 50 laccase/diphenol oxidase family protein
NCES-141 miR398c Medtr4g114870.1 3 8 21 38.1 plastocyanin-like domain protein
NCES-141 miR398a-3p Medtr8g064810.1 3 47 89 52.8 protein disulfide isomerase (PDI)-like protein
NCES-141 miR398c Medtr5g089180.1 3 4 19 21.1 hypothetical protein
NCES-141 miR408-3p Medtr8g089110.1 3 9 18 50 basic blue-like protein
NCES-141 miR408-3p Medtr8g007020.1 3.5 7 209 3.4 plastocyanin-like domain protein
NCES-141 miR408-3p Medtr8g007035.1 3.5 8 381 2.1 plastocyanin-like domain protein
NCES-141 miR408-5p Medtr3g074830.1 3.5 14 703 2 phosphate-responsive 1 family protein
NCES-141 miR482-3p Medtr5g027900.1 2.5 1 19 5.3 disease resistance protein (CC-NBS-LRR class) family protein
NCES-141 miR530 Medtr3g072110.1 2.5 1 119 0.8 transmembrane amino acid transporter family protein
NCES-141 miR1510a-5p Medtr7g108860.4 3.5 17 746 2.3 CS domain protein
NCES-141 miR2643a Medtr3g010620.1 1 2 72 2.8 F-box protein interaction domain protein
NCES-141 miR4414a-5p Medtr3g117120.1 4 2 134 1.5 BZIP transcription factor bZIP124
NCES-141 miR5037c Medtr4g070550.1 3 1 36 2.8 F-box protein interaction domain protein
NCES-141 miR5213-5p Medtr6g084370.1 2 1 5 20 disease resistance protein (TIR-NBS-LRR class)
NCES-141 miR5213-5p Medtr4g014580.1 1.5 1 18 5.6 TIR-NBS-LRR class disease resistance protein
NCES-141 miR5213-5p Medtr6g088245.1 3 1 7 14.3 disease resistance protein (TIR-NBS-LRR class)
NCES-141 miR5238 Medtr3g077740.2 2.5 1 151 0.7 pantothenate kinase
NCES-141 miR5561-3p Medtr2g045295.1 3 1 9 11.1 hypothetical protein
NCES-141 miR5752b Medtr8g066820.1 4 8 765 1.1 PLATZ transcription factor family protein
NCES-141 miR7696a-5p Medtr1g072130.1 3 2 135 1.5 PHD finger protein, putative
NCES-141 miR7696c-5p Medtr7g076830.1 3 5 78 6.4 DEAD-box ATP-dependent RNA helicase-like protein
NCES-141 miR7696d-5p Medtr3g112250.1 3.5 9 44 20.5 hypothetical protein
NCES-141 miR7696c-3p Medtr4g011600.2 3.5 1 124 0.8 sulfate transporter-like protein
NCES-141 miR7696c-3p Medtr7g085650.4 3.5 1 10 10 sulfate adenylyltransferase subunit 1/adenylylsulfate kinase
NCES-141 miR7701-3p Medtr3g108910.1 2.5 2 444 0.5 hypothetical protein
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The identified miRNA targets in all three genotypes include mainly transcription factors. Specifically, five members of the squamosa promoter-binding-like protein (SPL) targeted by the miR156 family, five members of the auxin response factors targeted by both miR160 and miR167 families, five members of the apetala2 (AP2)-domain containing transcription factors, four members of the growth-regulating factor (GRFs) family targeted by miR396, two members of the TCP family transcription factors targeted by miR319, and, a NAC domain-containing transcription factor-like protein (NAC) targeted by miR164 [35]. Additionally, transcripts encoding Argonaute targeted by miR168, laccase targeted by miR397, and three plantacyanin containing proteins targeted by miR408 were also identified. Although evidence indicates that that miR398 targets Cu/Zn superoxide dismutases and a copper chaperone for the superoxide dismutases (CCS) in plants [28, 38] these relationships were not apparent in the data from this study. On the other hand, we have identified three potentially non-conserved targets (plastocyanin, protein disulphide isomerase and a hypothetical protein) for miR398 in three alfalfa genotypes. In addition to the GRFs, our analyses revealed potential non-conserved targets for miR396 including TNP1, Ulp1 protease and hypothetical proteins (Table 5).

The analyses of legume-specific miRNAs and their targets have revealed an interesting miRNA: target networks between the miRNAs and the NBS-LRR genes [14, 16, 18, 32]. In this study, we identified NBS-LRR disease resistance genes as targets for four different miRNA families including miR482, miR1507, miR1510 and miR5213 in alfalfa (Table 5).

Degradome analyses has also been utilized to identify potential targets for several non-conserved miRNAs or miRNAs that are present only in closely related species such as the M. truncatula. To increase the confidence in identification of targets for the non-conserved miRNAs that are usually expressed at low abundances and the cleavage frequencies on those targets are relatively low, we considered as ‘targets’ only those for which the cleavages were detected at least in two of the three alfalfa genotypes. The transcripts for Medtr6g053240.1 (F-box protein interaction domain protein) had a cleavage frequency of approximately 75% and were targeted by the miR2643 in NF08ALF06 genotype. Additionally, two other F-box protein interaction domain protein genes were also identified as targets for miR2643 in alfalfa genotypes (Table 5). These results suggest that the F-box protein interaction domain protein family are regulated by this potential legume-specific miRNA. Another notable observation is that 6 different genes identified as potential targets for miR7696, and the cleavage frequency of a particular target gene (hypothetical protein, Medtr3g112250.1) was more abundant in all three alfalfa genotypes (Table 5).

Because some of the miRNA-stars are also highly expressed, we scrutinized the degradome reads for potential cleavages on the transcripts that are complementary to the miRNA-stars. This analysis has identified potential targets for at least four conserved miRNAs. Specifically, miR156-star targets a heat shock transcription factor, miR164-star targets a protein transporter Sec61 subunit alpha-like protein, miR167-star targets a GRAS family transcription factor, and, miR482-star targets an auxin response factor 1 in alfalfa (Table 5).

The confirmed targets of conserved miRNAs are known to regulate diverse developmental processes in the lifecycle of plants. For example, the SPL transcription factors (target of miR156) which regulate the transition from juvenile to adult phase of the life cycle in land plants [39]. Auxin receptors (TIR1 proteins) and ARFs targeted by miR393 and miR160, miR167, are components of the auxin signalling pathway that regulates several aspects of plant growth and development. The roles of NAC factors (targeted by miR164) include shoot meristem initiation and later root formation in Arabidopsis [40, 41]. Similarly, TCP family transcription factors have several different roles including regulating leaf morphogenesis [42, 43]. In Arabidopsis, seven out of nine GRFs are known targets for miR396 [44], and we have identified four GRFs as targets for miR396 in alfalfa (Table 5). By interacting with its coactivators called GRF-interacting factors (GIFs), this regulatory network (miR396-GRFs-GIFs) regulate leaf size, leaf growth and senescence in Arabidopsis [44]. The known targets for miR397 include laccase, which is involved in oxidative polymerization of lignin in plants [45]. Similarly, miR408 is targeting a family of plantacyanins, which could function in shuttling electron-transfer between proteins [46, 47].

The miR398 family is known to target CSDs and a copper chaperone for superoxide dismutase (CCS) genes in plants [28, 38]. In this study, we have identified plastocyanin-domain like proteins (plastocyanin is an essential electron carrier which shuttles the electrons between cytochrome b6f and PS I) represents a novel target for miR398. Protein disulphide isomerase (PDI) is a member of a family of dithiol/disulfide oxidoreductases, the thioredoxin superfamily, which functions in the formation of disulphide linkage between the cysteine residues for proper protein folding [48]. Our degradome analyses confirms that PDI represents a novel target for miR398 in alfalfa (Table 5). The other confirmed miRNA target transcripts include Leucine rich repeat resistance (LRR) proteins (TIR-NBS-LRR and CC-NBS-LRR) that play important roles in plant pathogen recognition and activation of plant innate immune responses [14, 16, 18, 32]. Yet another interesting target include the F-box protein interaction domain proteins that are regulated by miR2643, one of the very abundantly expressed miRNA in alfalfa.

Conclusions

The analyses of small RNA libraries from the whole plants, shoots and roots resulted in the identification of 100 miRNA families that included highly conserved miRNAs as well as miRNAs that are at least conserved between M. truncatula and alfalfa. The conserved miRNA profiles share some similarities and a few differences between genotypes and types of tissues (roots and shoots). The tissue-specific profiles were used to identify miRNAs that are highly abundant as well as those miRNAs that are expressed at low levels. Additionally, 17 novel miRNAs with varying levels of expression were also identified in alfalfa. The present study also reports identification of 69 targets for 31 miRNA families. In addition to the conserved targets for conserved miRNAs, a few non-conserved targets such as the PDI for miR398 were confirmed. Similarly, miR2643 is targeting three transcripts encoding F-box protein interaction domain containing proteins in alfalfa. In summary, the results from this study have increased our understanding of miRNAs and miRNA-mediated gene regulation in alfalfa that could result in potential tangible targets for practical applications in alfalfa and related legume species to increase biomass yield and address abiotic and biotic limitations to agricultural productivity.

Acknowledgements

Not applicable.

Funding

This research was funded by the Noble Research Institute and Forage Genetics International, a hatch grant from NIFA-0229360 (OKL02844) to RS and MM, and the National Natural Science Foundation of China (numbers 31460295 and 31760314) to YZ. This work was also partially supported by the Neustadt-Sarkeys Distinguished Professorship to RS. Publication costs are funded by the Oklahoma Agricultural Experiment Station, Oklahoma State University, Stillwater.

Availability of data and materials

The small RNA and degradome datasets generated and analyzed in the present study are available in the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) under accession number GSE119460 available at: https://www.ncbi.nlm.nih.gov/geo/query/511acc.cgi?acc=GSE119460.

About this supplement

This article has been published as part of BMC Genomics Volume 19 Supplement 10, 2018: Proceedings of the 29th International Conference on Genome Informatics (GIW 2018): genomics. The full contents of the supplement are available online at https://bmcgenomics.biomedcentral.com/articles/supplements/volume-19-supplement-10.

Authors’ contributions

RS and MM conceived the idea and designed the study. CM and TH cultured the plants used in this study; RP isolated the RNA from samples and generated the small RNA libraries; YZ, SR, QW, SA and RS analyzed the small RNA and degradome libraries; RP, SA and RS wrote the manuscript; MM edited the manuscript. All authors reviewed and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Robert Pokoo, Email: robertpokoo@gmail.com.

Shuchao Ren, Email: 18469100972@163.com.

Qingyi Wang, Email: wqy19941211@163.com.

Christy M. Motes, Email: cmmotes@noble.org

Timothy D. Hernandez, Email: tdhernandez@noble.org

Sayvan Ahmadi, Email: sayvan@okstate.edu.

Maria J. Monteros, Email: mjmonteros@noble.org

Yun Zheng, Email: zhengyun5488@gmail.com.

Ramanjulu Sunkar, Phone: 405-744-8496, Email: ramanjulu.sunkar@okstate.edu.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The small RNA and degradome datasets generated and analyzed in the present study are available in the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) under accession number GSE119460 available at: https://www.ncbi.nlm.nih.gov/geo/query/511acc.cgi?acc=GSE119460.

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